Incorporating Physical Information into Clustering for FPGAs

The traditional approach to FPGA clustering and CLB-level placement has been shown to yield significantly worse overall placement quality than approaches which allow BLEs to move during placement. In practice, however, modern FPGA architectures require computationally-expensive Design Rule Checks (DRC) which render BLE-level placement impractical. This thesis research addresses this problem by proposing a novel clustering framework that produces better initial clusters that help to reduce the dependence on BLE-level placement. The work described in this dissertation includes: (1) a comparison of various clustering algorithms used for FPGAs, (2) the introduction of a novel hybridized clustering framework for timing-driven FPGA clustering, (3) the addition of physical information to make better clusters, (4) a comparison of the implemented approaches to known clustering tools, and (5) the implementation and evaluation of cluster improvement heuristics. The proposed techniques are quantified across accepted benchmarks and show that the implemented DPack produces results with 16% less wire length, 19% smaller minimum channel widths, and 8% less critical delay, on average, than known academic tools. The hybridized approach, HDPack, is found to achieve 21% less wire length, 24% smaller minimum channel widths, and 6% less critical delay, on average

Algorithms for the scaling toward nanometer VLSI physical synthesis

Along the history of Very Large Scale Integration (VLSI), we have successfully scaled down the size of transistors, scaled up the speed of integrated circuits (IC) and the number of transistors in a chip - these are just a few examples of our achievement in VLSI scaling. It is projected to enter the nanometer (timing estimation and buffer planning for global routing and other early stages such as floorplanning. A novel path based buffer insertion scheme is also included, which can overcome the weakness of the net based approaches. Part-2 Circuit clustering techniques with the application in Field-Programmable Gate Array (FPGA) technology mapping The problem of timing driven n-way circuit partitioning with application to FPGA technology mapping is studied and a hierarchical clustering approach is presented for the latest multi-level FPGA architectures. Moreover, a more general delay model is included in order to accurately characterize the delay behavior of the clusters and circuit elements

Broadening the Scope of Multi-Objective Optimizations in Physical Synthesis of Integrated Circuits.

In modern VLSI design, physical synthesis tools are primarily responsible for satisfying chip-performance constraints by invoking a broad range of circuit optimizations, such as buffer insertion, logic restructuring, gate sizing and relocation. This process is known as timing closure. Our research seeks more powerful and efficient optimizations to improve the state of the art in modern chip design. In particular, we integrate timing-driven relocation, retiming, logic cloning, buffer insertion and gate sizing in novel ways to create powerful circuit transformations that help satisfy setup-time constraints. State-of-the-art physical synthesis optimizations are typically applied at two scales: i) global algorithms that affect the entire netlist and ii) local transformations that focus on a handful of gates or interconnections. The scale of modern chip designs dictates that only near-linear-time optimization algorithms can be applied at the global scope — typically limited to wirelength-driven placement and legalization. Localized transformations can rely on more time-consuming optimizations with accurate delay models. Few techniques bridge the gap between fully-global and localized optimizations. This dissertation broadens the scope of physical synthesis optimization to include accurate transformations operating between the global and local scales. In particular, we integrate groups of related transformations to break circular dependencies and increase the number of circuit elements that can be jointly optimized to escape local minima. Integrated transformations in this dissertation are developed by identifying and removing obstacles to successful optimizations. Integration is achieved through mapping multiple operations to rigorous mathematical optimization problems that can be solved simultaneously. We achieve computational scalability in our techniques by leveraging analytical delay models and focusing optimization efforts on carefully selected regions of the chip. In this regard, we make extensive use of a linear interconnect-delay model that accounts for the impact of subsequent repeated insertion. Our integrated transformations are evaluated on high-performance circuits with over 100,000 gates. Integrated optimization techniques described in this dissertation ensure graceful timing-closure process and impact nearly every aspect of a typical physical synthesis flow. They have been validated in EDA tools used at IBM for physical synthesis of high-performance CPU and ASIC designs, where they significantly improved chip performance.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78744/1/iamyou_1.pd

Impact of Multi-level Clustering on Performance Driven Global Placement

Delay and wirelength minimization continue to be important objectives in the design of high-performance computing systems. For large-scale circuits, the clustering process becomes essential for reducing the problem size. However, to the best of our knowledge, there is no study about the impact of multi-level clustering on performance-driven global placement. In this paper, five clustering algorithms including the quasi-optimal retiming delay driven PRIME and the cutsize-driven ESC have been considered for their impact on state-of-the-art mincut based global placement. Results show that minimizing cutsize or wirelength during clustering typically results in significant performance improvements

Simultaneous timing driven clustering and placement for FPGAs

Abstract. Traditional placement algorithms for FPGAs are normally carried out on a fixed clustering solution of a circuit. The impact of clustering on wirelength and delay of the placement solutions is not well quantified. In this paper, we present an algorithm named SCPlace that performs simultaneous clustering and placement to minimize both the total wirelength and longest path delay. We also incorporate a recently proposed path counting-based net weighting schem

Polyploidy breaks speciation barriers in Australian burrowing frogs Neobatrachus

Polyploidy has played an important role in evolution across the tree of life but it is still unclear how polyploid lineages may persist after their initial formation. While both common and well-studied in plants, polyploidy is rare in animals and generally less understood. The Australian burrowing frog genus Neobatrachus is comprised of six diploid and three polyploid species and offers a powerful animal polyploid model system. We generated exome-capture sequence data from 87 individuals representing all nine species of Neobatrachus to investigate species-level relationships, the origin and inheritance mode of polyploid species, and the population genomic effects of polyploidy on genus-wide demography. We describe rapid speciation of diploid Neobatrachus species and show that the three independently originated polyploid species have tetrasomic or mixed inheritance. We document higher genetic diversity in tetraploids, resulting from widespread gene flow between the tetraploids, asymmetric inter-ploidy gene flow directed from sympatric diploids to tetraploids, and isolation of diploid species from each other. We also constructed models of ecologically suitable areas for each species to investigate the impact of climate on differing ploidy levels. These models suggest substantial change in suitable areas compared to past climate, which correspond to population genomic estimates of demographic histories. We propose that Neobatrachus diploids may be suffering the early genomic impacts of climate-induced habitat loss, while tetraploids appear to be avoiding this fate, possibly due to widespread gene flow. Finally, we demonstrate that Neobatrachus is an attractive model to study the effects of ploidy on the evolution of adaptation in animals